A new multi-stage technique is presented for segmentation of targets of interest in synthetic aperture radar (SAR) data. The method creates an initial coarse segmentation using a histogram-based approach that labels each pixel as foreground or background. The extents of targets of interest are then determined using a hierarchical clustering stage that utilizes a novel weighting of intensity and pixel position. Finally, each potential target's segmentation is improved using probabilistic relaxation labeling. The approach loosens the typical region-based segmentation paradigm that only contiguous pixels can compose a segment. The technique is useful both for target segmentation and as a pre-processing step to verify the fidelity of artificially-generated data with real data.